compute.cumulative.multiple {mosclust} | R Documentation |
Function to compute the empirical cumulative distribution function (ECDF) of the similarity measures.
Description
The function compute.cumulative.multiple
computes the empirical cumulative distribution function (ECDF) of the similarity measures
for different number of clusters between clusterings.
The function cumulative.values
returns the values of the empirical cumulative distribution
Usage
compute.cumulative.multiple(sim.matrix)
cumulative.values(Fun)
Arguments
sim.matrix |
a matrix that stores the similarity between pairs of clustering across multiple number of clusters and multiple clusterings. Each row corresponds to a different number of clusters; number of columns equal to the number of subsamples considered for each number of clusters. |
Fun |
Function of class ecdf that stores the discrete values of the cumulative distribution |
Value
Function compute.cumulative.multiple
: a list of function of class ecdf.
Function cumulative.values
: a list with two elements: the "x" element stores a vector with the values of the random variable for
which the cumulative distribution needs to be computed; the "y" element stores a vector with the corresponding
values of the cumulative distribution (i.e. y = F(x)).
Author(s)
Giorgio Valentini valentini@di.unimi.it
See Also
Examples
library("clusterv")
# Data set generation
M <- generate.sample6 (n=20, m=10, dim=1000, d=3, s=0.2);
# generation of multiple similarity measures by resampling
Sr.kmeans.sample6 <- do.similarity.resampling(M, c=10, nsub=20, f=0.8, s=sFM,
alg.clust.sim=Kmeans.sim.resampling);
# computation of multiple ecdf (from 2 to 10 clusters)
list.F <- compute.cumulative.multiple(Sr.kmeans.sample6);
# values of the ecdf for 8 clusters
l <- cumulative.values(list.F[[7]])